6 citations · 12 across the 5 of their papers we have counts for
5 papers
MaLViL: Multi-axis Low-rank Vision-LSTM for Medical Image Segmentation
Afshin Bozorgpour, Sina Ghorbani Kolahi, Moein Heidari +2
Vision-LSTM (ViL) enables efficient global modeling, but its cost still scales with the number of spatial tokens, so existing segmenters confine ViL to a coarse bottleneck and lose…
CENet: Context Enhancement Network for Medical Image Segmentation
Afshin Bozorgpour, Sina Ghorbani Kolahi, Reza Azad +2
Medical image segmentation, particularly in multi-domain scenarios, requires precise preservation of anatomical structures across diverse representations. While deep learning has a…
MSANet: Multi-scale Adaptive Attention-guided Network for Medical Image Segmentation
Sina Ghorbani Kolahi, Seyed Kamal Chaharsooghi, Toktam Khatibi +5
Medical image segmentation involves identifying and separating object instances in a medical image to delineate various tissues and structures, a task complicated by the significan…
Computation-Efficient Era: A Comprehensive Survey of State Space Models in Medical Image Analysis
Moein Heidari, Sina Ghorbani Kolahi, Sanaz Karimijafarbigloo +8
Sequence modeling plays a vital role across various domains, with recurrent neural networks being historically the predominant method of performing these tasks. However, the emerge…
Enhancing Efficiency in Vision Transformer Networks: Design Techniques and Insights
Moein Heidari, Reza Azad, Sina Ghorbani Kolahi +8
Intrigued by the inherent ability of the human visual system to identify salient regions in complex scenes, attention mechanisms have been seamlessly integrated into various Comput…